{"id":131,"date":"2009-03-16T14:20:21","date_gmt":"2009-03-16T21:20:21","guid":{"rendered":"http:\/\/www.showcasemarketing.com\/ideablog\/?p=131"},"modified":"2022-11-15T05:34:57","modified_gmt":"2022-11-15T13:34:57","slug":"drilling-down-on-web-marketing-statistics-through-profiles","status":"publish","type":"post","link":"https:\/\/www.showcasemarketing.com\/ideablog\/drilling-down-on-web-marketing-statistics-through-profiles\/","title":{"rendered":"Drilling Down on Web Marketing Statistics Through Profiles"},"content":{"rendered":"

(updated in May 2016 with deeper information on types of web marketing metrics. The article continues to use the term “profiles,” though “personas” is the current rage.)<\/strong><\/em><\/p>\n

I envy the statistical information available to baseball managers. Elias Sports Bureau<\/a> provides major league teams with clean and consistent data for every single pitch: who\u2019s pitching, who\u2019s hitting, pitch thrown, inning, count, temperature and much more.<\/p>\n

Not so with marketing analytics statistics. The main limitation Web marketers face today is that the analysis data set available in aggregate form. I\u2019ll leave it to others to debate merits of Internet privacy protection<\/a> and marketing analytics. My focus is getting the most out of the available data.<\/p>\n

\"Web<\/p>\n

The antidote to aggregate data sets is to build profiles of target buyers, perform drill-down analyses on the profile\u2019s data segment and disproportionally attract users to your site that are within your profile.<\/p>\n

Profiles in Success<\/h3>\n

Consumer marketers have managed to profiles for years focusing on statistics like gender, age, income and geography. These profiles remain critical today for print and television advertising efficiency. They are less useful on the Web and with B2B purchases. As Peter Steiner\u2019s New Yorker cartoon famously states, \u201cOn the Internet, no one knows you\u2019re a dog<\/a>.\u201d In other words, you need to create profiles based on the data you have, not the data you choose.<\/p>\n

When defining profiles, remember the goals of your analytics efforts:<\/p>\n

    \n
  1. Ensure you are attracting a sufficient number of visitors who match your profile to your web site in a given period<\/li>\n<\/ol>\n

    \"Earn<\/p>\n

      \n
    1. Measure visitor satisfaction with the information on your web site.<\/li>\n
    2. Excel at persuading visitors in your profile to provide you with contact information. In marketing parlance: convert<\/a>.<\/li>\n<\/ol>\n

      For B2B enterprise software purchases, sales and executive teams have learned to appreciate profiles based on the following web statistics:<\/p>\n